基于出行意图的潜在高价值旅客发现概率模型

doi:10.13190/j.jbupt.2018-016

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (1): 81-86.doi: 10.13190/j.jbupt.2018-016

基于出行意图的潜在高价值旅客发现概率模型

徐涛^1,2,3, 张继水^1,2, 卢敏^1,2,3,4

1. 中国民航大学计算机科学与技术学院, 天津 300300;
2. 中国民航大学中国民航信息技术科研基地, 天津 300300;
3. 民航旅客服务智能化应用技术重点实验室, 北京 101318;
4. 中山大学机器智能与先进计算教育部重点实验室, 广州 510275

收稿日期:2018-01-14 出版日期:2019-02-28 发布日期:2019-03-08
作者简介:徐涛(1962-),男,教授,博士生导师,E-mail:txu@cauc.edu.cn.
基金资助:
国家自然科学基金项目（61502499）；中山大学机器智能与先进计算教育部重点实验室开放课题（MSC-201704A）；中国民航大学科研启动项目（2013QD18X）

A Probabilistic Model for Discovering Potential High-Value Passengers Based on Trip Purposes Mining

XU Tao^1,2,3, ZHANG Ji-shui^1,2, LU Min^1,2,3,4

1. College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China;
2. Information Technology Research Base of Civil Aviation Administration of China, Civil Aviation University of China, Tianjin 300300, China;
3. Key Laboratory of Intelligent Passenger Service of Civil Aviation, Beijing 101318, China;
4. Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Guangzhou 510275, China

Received:2018-01-14 Online:2019-02-28 Published:2019-03-08
Supported by:

摘要/Abstract

摘要： 由于潜在高价值旅客当前乘机历史记录少，较难被航空公司准确发现并关注.对此，提出基于出行意图的潜在高价值旅客发现概率模型.首先建立一个基于统计的潜在高价值旅客发现概率模型，再将旅客出行意图引入概率模型，发现旅客潜在航线需求，优化旅客潜在价值计算，从而通过出行意图发现潜在高价值旅客.实验结果表明，相比于次数法、里程法以及RFM模型等传统的旅客价值度量方法，基于出行意图的潜在高价值旅客发现概率模型能够有效识别潜在高价值旅客.

关键词: 民航旅客, 概率模型, 出行意图, 潜在价值, 潜在航线需求

Abstract: Potential high-value passengers can not be effectively discovered by airways due to the limited historical booking records of passengers. Aiming at this problem, a probabilistic model for discovering potential high-value passengers based on trip purposes mining is proposed. Firstly, we present a probabilistic model based on statistics to measure the value of passengers. Then, trip purposes are introduced into the model to discover potential airline demands of each passenger and to optimize passenger potential value calculation. Therefore, potential high-value passengers can be discovered through the trip purposes mining. Experiments show that the proposed model can identify the potential high-value passengers more accurately than the traditional passenger value evaluation methods based on the passengers' cumulative number of flight times, passengers' cumulative mileage and recency frequency monetry model.

Key words: civil aviation passengers, probabilistic model, trip purposes, potential value, potential airline demand

中图分类号:

TP399

徐涛, 张继水, 卢敏. 基于出行意图的潜在高价值旅客发现概率模型[J]. 北京邮电大学学报, 2019, 42(1): 81-86.

XU Tao, ZHANG Ji-shui, LU Min. A Probabilistic Model for Discovering Potential High-Value Passengers Based on Trip Purposes Mining[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(1): 81-86.

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基于出行意图的潜在高价值旅客发现概率模型

A Probabilistic Model for Discovering Potential High-Value Passengers Based on Trip Purposes Mining

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